Specific topics:
- Scenario creation
- Input data
- Output data and result analysis
- Model description
- Example: 9 bus case (Jupyter notebook)
- Example: Europe 2014 (Jupyter notebook)
PowerGAMA is open source software created by SINTEF Energy Research. The expanded name is Power Grid And Market Analysis. This is a Python-based lightweight simulation tool for high level analyses of renewable energy integration in large power systems.
The simulation tool optimises the generation dispatch, i.e. the power output from all generators in the power system, based on marginal costs for each timestep for a given duration. It takes into account the variable power available for solar, hydro and wind power generators. It also takes into account the variability of demand. Moreover, it is flow-based meaning that the power flow in the AC grid is determined by physical power flow equations.
Since some generators may have an energy storage (hydro power with reservoir and concentrated solar power with thermal storage) the optimal solution in one timestep depends on the previous timestep, and the problem should therefore be solved sequentially. A realistic utilisation of energy storage is ensured through the use of storage values.
PowerGAMA does not include any power market subtleties (such as start-up costs, limited ramp rates, forecast errors, unit commitments) and as such will tend to overestimate the ability to accommodate large amounts of variable renewable energy. Essentially it assumes a perfect market based on nodal pricing without barriers between different countries. This is naturally a gross oversimplification of the real power system, but gives nonetheless very useful information to guide the planning of grid developments and to assess broadly the impacts of new generation and new interconnections.
PowerGAMA is open source software distributed under the MIT License,
PowerGAMA is a Python package. It requires
- Python 3
- A solver (e.g. the free CBC solver or the GLPK solver)